Methods and apparatus to generate a signature based on signature candidates

ABSTRACT

Methods, apparatus, systems and articles of manufacture are disclosed to generate a signature based on signature candidates. An example apparatus disclosed herein includes first means for determining an alignment point of a first candidate signature segment and a second candidate signature segment, the first candidate signature segment and the second candidate signature segment include time data and signature data, the alignment point based on the time data of the first candidate signature segment and the time data of the second candidate signature segment, means for comparing a first signature to a second signature at the alignment point, the first signature representative of media included in the first candidate signature segment, the second signature included in the second candidate signature segment, and means for stitching the second signature to the first signature based on the comparison to generate a stitched signature, the stitched signature to be used for media crediting.

RELATED APPLICATION

This patent arises from a continuation of U.S. patent application Ser.No. 17/331,603, which was filed on May 26, 2021. Priority to U.S. patentapplication Ser. No. 17/331,603 is claimed. U.S. patent application Ser.No. 17/331,603 is hereby incorporated by reference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media monitoring, and, moreparticularly, to methods and apparatus to generate a signature based onsignature candidates.

BACKGROUND

A media monitoring entity can generate audio signatures from a mediasignal. Audio signatures are a condensed reference that can be used tosubsequently identify the media. These signatures can be hashed to allowfaster matching in an audio signature database. In some examples, amedia monitoring entity can monitor a media source feed (e.g., atelevision feed, etc.) to generate reference signatures representativeof media presented via that media source feed. Such reference signaturescan be compared to signatures generated by media monitors to creditviewership of the media.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of an example media monitoring systemconstructed in accordance with teachings of this disclosure to monitormedia.

FIG. 2 is a schematic illustration of an example meter data analyzerincluded in the example media monitoring system of FIG. 1 .

FIG. 3 is an example illustration of an example first candidatesignature segment and an example second candidate signature segment.

FIG. 4 is an example illustration of an example first candidatesignature segment and an example second candidate signature segment thatoverlap.

FIG. 5 is an example illustration of an example stitched signaturegenerated in accordance with teachings of this disclosure based on thefirst candidate signature segment and the second candidate signaturesegment of FIG. 4 .

FIG. 6 . is an example illustration of an example reference signatureand an example stitched signature that is validated.

FIG. 7 is an example illustration of an example reference signature andan example stitched signature that is not validated.

FIG. 8 is a flowchart representative of machine-readable instructionswhich may be executed to implement the example meter data analyzer ofFIGS. 1 and/or 2 to perform signature stitching.

FIG. 9 is a flowchart representative of machine-readable instructionswhich may be executed to implement an example signature matcher of FIG.2 to perform signature-by-signature matching.

FIG. 10 is a flowchart representative of machine-readable instructionswhich may be executed to implement an example candidate stitcher of FIG.2 to stitch candidate signature segments together.

FIG. 11 is a flowchart representative of machine-readable instructionswhich may be executed to implement an example stitching validator ofFIG. 2 to validate stitched signatures.

FIG. 12 is a block diagram of an example processing platform structuredto execute the instructions of FIGS. 8-11 to implement the example meterdata analyzer of FIGS. 1 and/or 2 .

FIG. 13 is a block diagram of an example software distribution platformto distribute software (e.g., software corresponding to the examplecomputer readable instructions of FIGS. 8-11 ) to client devices such asconsumers (e.g., for license, sale and/or use), retailers (e.g., forsale, re-sale, license, and/or sub-license), and/or original equipmentmanufacturers (OEMs) (e.g., for inclusion in products to be distributedto, for example, retailers and/or to direct buy customers.

The figures are not to scale. In general, the same reference numberswill be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts.

Unless specifically stated otherwise, descriptors such as “first,”“second,” “third,” etc. are used herein without imputing or otherwiseindicating any meaning of priority, physical order, arrangement in alist, and/or ordering in any way, but are merely used as labels and/orarbitrary names to distinguish elements for ease of understanding thedisclosed examples. In some examples, the descriptor “first” may be usedto refer to an element in the detailed description, while the sameelement may be referred to in a claim with a different descriptor suchas “second” or “third.” In such instances, it should be understood thatsuch descriptors are used merely for identifying those elementsdistinctly that might, for example, otherwise share a same name. As usedherein “substantially real time” refers to occurrence in a nearinstantaneous manner recognizing there may be real world delays forcomputing time, transmission, etc. Thus, unless otherwise specified,“substantially real time” refers to real time +/−1 second.

DETAILED DESCRIPTION

As used herein, the term “media” includes any type of content and/oradvertisement delivered via any type of distribution medium. Thus, mediaincludes television programming or advertisements, radio programming oradvertisements, movies, web sites, streaming media, etc.

Example methods, apparatus, and articles of manufacture disclosed hereinmonitor media presentations at media devices. Such media devices mayinclude, for example, Internet-enabled televisions (e.g., smarttelevisions), televisions with an Internet enablement attached (e.g., atelevision with a Roku®), personal computers, Internet-enabled mobilehandsets (e.g., a smartphone), video game consoles (e.g., Xbox®,PlayStation®), tablet computers (e.g., an iPad®), digital media players(e.g., a Roku® media player, a Slingbox®, etc.), etc.

In some examples, media monitoring information is aggregated todetermine ownership and/or usage statistics of media devices, determinethe media presented by the media devices, determine audience ratings,determine relative rankings of usage and/or ownership of media devices,determine types of uses of media devices (e.g., whether a device is usedfor browsing the Internet, streaming media from the Internet, etc.),and/or determine other types of media device information. In examplesdisclosed herein, monitoring information includes, but is not limitedto, one or more of media identifying information (e.g.,media-identifying metadata, codes, signatures, watermarks, and/or otherinformation that may be used to identify presented media), applicationusage information (e.g., an identifier of an application, a time and/orduration of use of the application, a rating of the application, etc.),identifying information (e.g., demographic information, a useridentifier, a panelist identifier, a username, etc.), etc.

Audio watermarking is a technique used to identify media, such astelevision broadcasts, radio broadcasts, advertisements (televisionand/or radio), downloaded media, streaming media, prepackaged media,etc. Existing audio watermarking techniques identify media by embeddingone or more audio codes (e.g., one or more watermarks), such as mediaidentifying information and/or an identifier that may be mapped to mediaidentifying information, into an audio and/or video component. In someexamples, the watermark is embedded in the audio or video component sothat the watermark is hidden. This embedding may be carried oututilizing psychoacoustic masking.

As used herein, the terms “code” or “watermark” are used interchangeablyand are defined to mean any identification information (e.g., anidentifier) that may be inserted or embedded in the audio or video ofmedia (e.g., a program or advertisement) for the purpose of identifyingthe media or for another purpose such as tuning (e.g., a packetidentifying header).

To identify watermarked media, the watermark(s) are extracted and usedto access a table of reference watermarks that are mapped to mediaidentifying information. In some examples, media monitoring companiesprovide watermarks and/or watermarking devices to media providers withwhich to encode their media source feeds. In some examples, if a mediaprovider provides multiple media source feeds (e.g., ESPN and ESPN 2,etc.), a media provider can provide a different watermark for each mediasource feed. In some examples, a media provider could encode a mediasource feed with an incorrect watermark (e.g., a watermark meant forESPN could accidentally be encoded on ESPN2, etc.). In this example,crediting using only watermarking could result in the wrong media sourcefeed being credited.

Unlike media monitoring techniques based on codes and/or watermarksincluded with and/or embedded in the monitored media, fingerprint orsignature-based media monitoring techniques generally use one or moreinherent characteristics of the monitored media during a monitoring timeinterval to generate a substantially unique proxy for the media. Such aproxy is referred to as a signature or fingerprint, and can take anyform (e.g., a series of digital values, a waveform, etc.) representativeof any aspect(s) of the media signal(s) (e.g., the audio and/or videosignals forming the media presentation being monitored). A signature maybe a series of signatures collected in series over a time interval. Agood signature is repeatable when processing the same mediapresentation, but is unique relative to other (e.g., different)presentations of other (e.g., different) media. Accordingly, the terms“fingerprint” and “signature” are used interchangeably herein and aredefined herein to mean a proxy for identifying media that is generatedfrom one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g.,generating and/or collecting) signature(s) representative of a mediasignal (e.g., an audio signal and/or a video signal) output by amonitored media device and comparing the monitored signature(s) to oneor more reference signatures corresponding to known (e.g., reference)media source feeds. Various comparison criteria, such as across-correlation value, a Hamming distance, etc., can be evaluated todetermine whether a monitored signature matches a particular referencesignature. When a match between the monitored signature and a referencesignatures is found, the monitored media can be identified ascorresponding to the particular reference media represented by thereference signature that matched the monitored signature. In someexamples, signature matching is based on sequences of signatures suchthat, when a match between a sequence of monitored signatures and asequence of reference signatures is found, the monitored media can beidentified as corresponding to the particular reference mediarepresented by the sequence of reference signatures that matched thesequence of monitored signatures. Because attributes, such as anidentifier of the media, a presentation time, a broadcast channel, etc.,are collected for the reference signature, these attributes may then beassociated with the monitored media whose monitored signature(s) matchedthe reference signature(s). Example systems for identifying media basedon codes and/or signatures are long known and were first disclosed inThomas, U.S. Pat. No. 5,481,294, which is hereby incorporated byreference in its entirety.

Media monitoring entities (e.g., The Nielsen Company (US), LLC, etc.)desire knowledge regarding how users interact with media devices such assmartphones, tablets, laptops, smart televisions, etc. In particular,media monitoring entities want to monitor media presentations made atthe media devices to, among other things, monitor exposure toadvertisements, determine advertisement effectiveness, determine userbehavior, identify purchasing behavior associated with variousdemographics, etc. Media monitoring entities can provide media meters topeople (e.g., panelists) which can generate media monitoring data basedon the media exposure of those users. Such media meters can beassociated with a specific media device (e.g., a television, a mobilephone, a computer, etc.) and/or a specific person (e.g., a portablemeter, etc.).

Media monitoring entities can generate media reference databases thatcan include unhashed signatures, hashed signatures, and watermarks.These references are generated by a media monitoring entity (e.g., at amedia monitoring station (MMS), etc.) by monitoring a media source feed,identifying any encoded watermarks and determining signatures associatedwith the media source feed.

In some examples, media monitoring entities store generated referencedatabases and gathered monitoring data on cloud storage services (e.g.,AMAZON WEB SERVICES®, etc.). To allow the crediting of time-shiftedviewing (e.g., viewing media via a digital video recorder (DVR), etc.),the stored references are retained for a period time after the initialpresentation of the media.

In some examples, the media monitoring entity can hash the determinedsignatures. Additionally or alternatively, the media monitoring entitiesgenerate reference signatures for downloaded reference media (e.g., froma streaming media provider), reference media transmitted to the mediamonitoring entity from one or more media providers, etc. That is, themedia monitoring entities can generate reference signatures of mediathat is not live broadcasted. In some examples, media that is not livebroadcasted includes a subscription video on demand (SVOD) asset. Asused herein, a “media asset” refers to any individual, collection, orportion/piece of media of interest (e.g., a commercial, a song, a movie,an episode of television show, etc.). Media assets can be identified viaunique media identifiers (e.g., a name of the media asset, a metadatatag, etc.). Media assets can be presented by any type of mediapresentation method (e.g., via streaming, via live broadcast, from aphysical medium, etc.).

The reference database can be compared (e.g., matched, etc.) to mediamonitoring data (e.g., watermarks, unhashed signatures, hashedsignatures, etc.) gathered by media meter(s) to allow crediting of mediaexposure. Monitored media can be credited using one, or a combination,of watermarks, unhashed signatures, and hashed signatures. Referencesignatures of the reference database are ideally generated using acomplete and uninterrupted (e.g., continuous) viewing of the mediaasset. However, waiting to receive a single, complete media asset cantake time, which is a limited commodity when generating a referencesignature for release day measurement, for example. If a media asset isnot in the reference database (e.g., a new episode in a series that doesnot yet have corresponding reference signatures stored in the referencedatabase), the media monitoring entity may be unable to credit the mediaexposure of the media asset.

However, media monitoring entities receive partial segments or fragmentsof an episode a panelist is watching. As used herein, a signaturesegment or signature fragment is a signature sequence of a media assetthat does not correspond to the entire duration of the media asset.Thus, two or more signature segments of a media asset can be stitchedtogether to form a signature sequence corresponding to the entireduration of the media asset. In prior techniques, signature segments arestitched together based on time of content data. For example, adjacentsignature segments are determined according to time of content data andstitched together. However, time of content data can be unreliableand/or inconsistent (e.g., different signature segments correspond todifferent clock specificity, etc.). If each signature segmentcorresponds to different time of content data, prior signature stitchingtechniques may incorrectly align and/or arrange signature segments suchthat the resulting signature sequence is not representative of thesignature sequence that was generated from an uninterrupted viewing(e.g., the corresponding reference signature). In such examples, theresulting stitched signature may have additional signatures and/or fewersignatures than the reference signature. Furthermore, these stitchingerrors may accumulate each time signature segments are stitchedtogether, resulting in a stitched signature sequence that does not matchthe reference signature and, thus, may not be recognized for mediacrediting. To increase accuracy of signature segment stitching, methods,apparatus, and systems disclosed herein stitch signature segments basedon an overlap between signature segments, instead of aligning signaturesegments based on time of content, thereby reducing incorrect stitchedsignature sequences.

Methods and apparatus disclosed herein enable crediting media based onsignature segments of media assets. Example techniques disclosed hereininclude determining whether signature segments meet a durationthreshold, the duration threshold to determine whether the signaturesegments are candidate signature segments for stitching. Disclosedexample techniques also include determining an overlap between thecandidate signature segments based on time data, the overlap torepresent similar time data shared between the candidate signaturesegments. Disclosed example techniques further include stitchingcandidate signature sequences together to generate stitched signatures,in response to determining (i) the number of strong matches between thesignature sequences of the overlap exceeds a first threshold and (ii)the number of basic matches between the signature sequences of theoverlap exceeds a second threshold. As used herein, “stitchedsignatures” are signature sequences of corresponding to the combinationof two or more candidate signature segments. Disclosed exampletechniques also include comparing stitched signatures to referencesignatures to validate the stitched signatures.

FIG. 1 is a schematic illustration of an example media monitoring system100 constructed in accordance with teachings of this disclosure tomonitor media. The example media monitoring system 100 includes anexample first media meter 102A, an example second media meter 102B, andan example third media meter 102C, which output example first monitoringdata 104A, example second monitoring data 104B, and example thirdmonitoring data 104C, respectively, to an example network 106. The mediamonitoring system 100 further includes an example data center 108, whichincludes an example meter data analyzer 110. In the illustrated example,the meter data analyzer 110 outputs identification data 112 to anexample media exposure creditor 114.

The example media meters 102A, 102B, 102C collect media monitoringinformation. In some examples, the media meters 102A, 102B, 102C areassociated with (e.g., installed on, coupled to, etc.) respective mediadevices. For example, a media device associated with one of the mediameters 102A, 102B, 102C presents media (e.g., via a display, etc.). Insome examples, the media device associated with one of the media meters102A, 102B, 102C additionally or alternatively presents the media onseparate media presentation equipment (e.g., speakers, a display, etc.).For example, the media device(s) associated with the media meters 102A,102B, 102C can include a personal computer, an Internet-enabled mobilehandsets (e.g., a smartphone, an iPod®, etc.), video game consoles(e.g., Xbox®, PlayStation 3, etc.), tablet computers (e.g., an iPad®, aMotorola™ Xoom™, etc.), digital media players (e.g., a Roku® mediaplayer, a Slingbox®, a Tivo®, etc.), televisions, desktop computers,laptop computers, servers, etc. In such examples, the media meters 102A,102B, 102C may have direct connections (e.g., physical connections) tothe devices to be monitored, and/or may be connected wirelessly (e.g.,via Wi-Fi, via Bluetooth, etc.) to the devices to be monitored.

Additionally or alternatively, in some examples, one or more of themedia meters 102A, 102B, 102C are portable meters carried by one or moreindividual people. In the illustrated example, the media meters 102A,102B, 102C monitor media presented to one or more people associated withthe media meters 102A, 102B, 102C and generate the example monitoringdata 104A, 104B, 104C. In some examples, monitoring data 104A, 104B,104C generated by the media meters 102A, 102B, 102C can includewatermarks detected in presented media. Such detected watermarks may bereferred to as monitored media watermarks or monitored watermarks asthey are detected in media monitored by the media meters 102A, 102B,102C. In some examples, the media meters 102A, 102B, 102C can determinesignatures associated with the presented media (e.g., signaturesegments, etc.). For example, the media meters 102A, 102B, 102C candetermine signatures (e.g., generate signatures, create signatures,etc.) representative of media presented on the associated media devices.Such signatures may be referred to as monitored media signatures ormonitored signatures as they are determined from media monitored by themedia meters 102A, 102B, 102C. In some examples, the monitoring data104A, 104B, 104C includes time data. For example, the monitoring data104A, 104B, 104C can include timestamps associated with each signatureof the monitoring data 104A, 104B, 104C. Accordingly, the monitoringdata 104A, 104B, 104C can include monitored media signatures and/ormonitored media watermarks representative of the media monitored by themedia meters 102A, 102B, 102C. In some examples, the monitoring data104A, 104B, 104C is associated with a discrete, measurement time period(e.g., five minutes, ten minutes, etc.). In such examples, themonitoring data 104A, 104B, 104C can include sequences of monitoredmedia signatures and/or sequences of monitored media watermarksassociated with media asset(s) (or portions thereof) presented by themedia devices monitored by the media meters 102A, 102B, 102C.

Example signature generation techniques that may be implemented by themedia meters 102A, 102B, 102C include, but are not limited to, examplesdisclosed in U.S. Pat. No. 4,677,466 issued to Lert et al. on Jun. 30,1987; U.S. Pat. No. 5,481,294 issued to Thomas et al. on Jan. 2, 1996;U.S. Pat. No. 7,460,684 issued to Srinivasan on Dec. 2, 2008; U.S. Pat.No. 9,438,940 issued to Nelson on Sep. 6, 2016; U.S. Pat. No. 9,548,830issued to Kariyappa et al. on Jan. 17, 2017; U.S. Pat. No. 9,668,020issued to Nelson et al. on May 30, 2017; U.S. Pat. No. 10,200,546 issuedto Nelson et al. on Feb. 5, 2019; U.S. Publication No. 2005/0232411 toSrinivasan et al. published on Oct. 20, 2005; U.S. Publication No.2006/0153296 to Deng published on Jul. 13, 2006; U.S. Publication No.2006/0184961 to Lee et al. published on Aug. 17, 2006; U.S. PublicationNo. 2006/0195861 to Lee published on Aug. 31, 2006; U.S. Publication No.2007/0274537 to Srinivasan published on Nov. 29, 2007; U.S. PublicationNo. 2008/0091288 to Srinivasan published on Apr. 17, 2008; and U.S.Publication No. 2008/0276265 to Topchy et al. published on Nov. 6, 2008.

The example network 106 is a network used to transmit the monitoringdata 104A, 104B, 104C to the data center 108. In some examples, thenetwork 106 can be the Internet or any other suitable external network.In other examples, the network 106 can be a cable broadcast system andthe monitoring data 104A, 104B, 104C could be return path data (RPD). Inother examples, any other communication path for transmitting themonitoring data 104A, 104B, 104C to the data center 108 can be used(e.g., a wired network, a wireless network, a local area network, a widearea network, etc.).

The example data center 108 is an execution environment used toimplement the example meter data analyzer 110 and the example mediaexposure creditor 114. In some examples, the data center 108 isassociated with a media monitoring entity. In some examples, the datacenter 108 can be a physical processing center (e.g., a central facilityof the media monitoring entity, etc.). Additionally or alternatively,the data center 108 can be implemented via a cloud service (e.g., AWS®,etc.). In this example, the data center 108 can further store andprocess generated watermark and signature reference data.

The example meter data analyzer 110 processes the gathered mediamonitoring data to detect, identify, credit, etc., respective mediaassets and/or portions thereof (e.g., media segments) associated withthe corresponding monitoring data 104A, 104B, 104C. For example, themeter data analyzer 110 can compare the monitoring data 104A, 104B, 104Cto generated reference data to determine what respective media isassociated with the corresponding monitoring data 104A, 104B, 104C. Themeter data analyzer 110 of the illustrated example also analyzes themonitoring data 104A, 104B, 104C to determine if the media asset(s),and/or particular portion(s) (e.g., segment(s)) thereof, associated withthe signature match is (are) to be credited. For example, the meter dataanalyzer 110 can compare monitored media signatures in the monitoringdata 104A, 104B, 104C to a library of generated reference signatures todetermine the media asset(s) associated with the monitored mediasignatures.

In response to not detecting a match between a sequence of the monitoredmedia signatures and a corresponding sequence of the referencesignatures, the meter data analyzer 110 can determine whether thesequence of the monitored media signatures meet candidate criteria. Forexample, the candidate criteria can be a time duration associated withthe signature segment. In some examples, if the signature segments meetthe candidate criteria, referred to herein as a candidate signaturesegment, the meter data analyzer 110 performs signature-by-signaturematching to determine whether the first candidate signature segment andthe second candidate signature segment overlap.

The example meter data analyzer 110 determines if the signaturesequences of the overlap between the first and second candidatesignature segments meet stitching criteria. For example, stitchingcriteria can be a number of strong matches, a number of basic matches,etc. In response to the signature sequences of the overlap meetingstitching criteria, the meter data analyzer 110 stitches the first andsecond candidate signature segments together to generate a stitchedsignature. In some examples, the meter data analyzer 110 validates thestitched signature. For example, the meter data analyzer 110 performssignature-by-signature matching of the stitched signature and areference signature (e.g., a signature of the media asset that wasgenerated continuously). An example implementation of the meter dataanalyzer 110 is described below in conjunction with FIG. 2 .

The example identification data 112 includes information to credituser(s) associated with the media meters 102A, 102B, 102C with exposureto one or more particular media assets. For example, the identificationdata 112 can include direct associations between monitoring data 104A,104B, 104C and one or more particular media assets. For example, theidentification data 112 can include media identifiers associated withthe media assets represented in the monitoring data 104A, 104B, 104C andtimestamps associated with the period of exposure to that media. Theexample media exposure creditor 114 uses the identification data 112 tocredit media with having been exposed to user(s). In some examples, themedia exposure creditor 114 generates a report including data metricsthat may be presented to media providers.

FIG. 2 is a schematic illustration of an example implementation of theexample meter data analyzer 110 included in the example media monitoringsystem 100 of FIG. 1 . The example meter data analyzer 110 of FIG. 2includes an example network interface 202, an example buffer 204, anexample signature handler 206, an example signature matcher 212, anexample candidate stitcher 218, an example reference signature database220, and an example stitching validator 222.

The example network interface 202 of the illustrated example of FIG. 2is communicatively connected to the example network 106 of FIG. 1 . Theexample network interface 202 provides connection between the examplemedia meters 102A, 102B, 102C and the example network 106. In someexamples, the example network interface 202 is implemented by hardware(e.g., a network interface card). In further examples, the examplenetwork interface 202 is implemented by software.

The example buffer 204 of the illustrated example of FIG. 2 stores(e.g., buffers, holds, etc.) incoming signatures. For example, thebuffer 204 stores signature segments accessed by the network interface202. The example buffer 204 may be implemented using any number and/ortype(s) of non-volatile, and/or volatile computer-readable storagedevice(s) and/or storage disk(s).

The example signature handler 206 of the illustrated example of FIG. 2determines whether signatures stored in the buffer 204 are candidatesignature segments. The example signature handler 206 includes anexample candidate checker 208 and an example timing handler 210.

The example candidate checker 208 determines whether signature segmentsstored in the buffer 204 are candidate signature segments. For example,the candidate checker 208 determines whether the signature segments arestored in the reference signature database 220. That is, a signaturesegment can correspond to the entire duration of a reference signature(e.g., the monitoring data 104A, 104B, 104C was generated based on anuninterrupted viewing of a media asset), a signature segment can match asegment of a reference signature (e.g., the signature segmentcorresponds to a reference signature already generated, the signaturesegment corresponds to a stitched signature segment, etc.), etc. Thus,if the signature segment matches signature sequences stored in thereference signature database 220, the signature segment is not acandidate signature segment.

If the example candidate checker 208 determines the signature segment isnot stored in the reference signature database 220, the candidatechecker 208 determines the time duration of the signature segment. Insome examples, the candidate checker 208 determines the time duration ofthe signature segment based on timestamps associated with the first andlast signatures of the signature segment. Thus, the example candidatechecker 208 may determine the time duration of the signature segment asthe difference between the timestamp of the last signature and thetimestamp of the first signature of the signature segment.

The example candidate checker 208 determines whether the time durationof the signature segment exceeds a candidate duration threshold. Thatis, the example candidate checker 208 determines whether the signaturesegment has a long enough duration to offset the computing resourcesused to stitch signatures together. For example, analyzing signaturesegments and stitching candidate signature segments together requirescomputing resources, such as memory and time. Thus, analyzing andstitching a relatively short signature segment (e.g., a signaturesegment with a time duration less than the candidate duration threshold)may not warrant the computing resources required. For example, asignature segment with a time duration of two seconds may not add enoughinformation to warrant the computing resources (e.g., the stitchedsignature segment cannot be used for crediting, etc.).

In examples disclosed herein, the candidate duration threshold is 60seconds. However, the candidate duration threshold can be shorter orlonger than 60 seconds. For example, the candidate checker 208determines a first signature segment stored in the buffer 204 has a timeduration of 30 seconds and a second signature segment stored in thebuffer 204 has a time duration of 70 seconds. The example candidatechecker 208 determines the first signature segment does not exceed thecandidate duration threshold and, thus, is not a candidate signaturesegment. The example candidate checker 208 determines the secondsignature segment does exceed the candidate duration threshold, and,thus, is a candidate signature segment.

In some examples, the candidate duration threshold varies. For example,the candidate checker 208 can increase and/or decrease the candidateduration threshold. In some examples, the candidate checker 208determines the candidate duration threshold based on one or more offeedback from validation (e.g., validation data), a lack of ability tostitch signature segments (e.g., a stitching ability), etc. For example,if the stitching validator 222 (described below) validates a stitchedsignature, the candidate checker 208 can decrease the candidate durationthreshold (e.g., decrease the candidate duration threshold to 50seconds, etc.).

The example timing handler 210 of the illustrated example of FIG. 2aligns a first candidate signature segment and a second candidatesignature segment based on time data. That is, the timing handler 210determines whether the first and second candidate signature segmentsoverlap based on time data. Thus, the example timing handler 210determines the starting point of the signature segment overlap (e.g., analignment point). For example, the timing handler 210 determines if asignature of the first candidate signature segment and a signature ofthe second candidate signature segment have similar timestamps. Forexample, the timing handler 210 determines if the timestamp of thesignature of the first candidate signature segment and the timestamp ofthe signature of the second candidate signature segment are within adeviation threshold from each other. For example, the deviationthreshold can be one (e.g., a first timestamp is +/−1 second from asecond timestamp). However, the deviation threshold can be two seconds,three seconds, etc.

The example timing handler 210 adjusts time of content data of stitchedsignatures. For example, after two candidate signature segments arestitched together, the time data after the stitching point (e.g., thetime data corresponding to the signatures of the second candidatesignature segment) may not be accurate. That is, at the stitching point,the timestamp of the last signature of the first candidate signaturesegment may be a greater number (e.g., a later time) than the timestampof the first signature of the second candidate signature segment.Additionally or alternatively, the timestamp between the first andsecond signature segments at the stitching point may be greater than thedeviation threshold, etc. The example timing handler 210 updates thetimestamps corresponding to the signatures of the second candidatesignature segment based on the timestamps corresponding to thesignatures of the first candidate signature segment. That is, when thefirst and second candidate signature segments are stitched together, thetimestamps of the second candidate signature segment is not inserted.

The example signature matcher 212 of the illustrated example of FIG. 2determines whether a first and second candidate signature segmentcorresponds to the same media asset. That is, the example signaturematcher 212 determines whether the overlapping signature segment of thefirst candidate signature segment matches the corresponding overlappingsignature segment of the second candidate signature segment. The examplesignature matcher 212 includes an example signature comparator 214 andan example signature match counter 216.

The example signature comparator 214 of the illustrated example of FIG.2 compares signatures of the first candidate signature segment tosignatures of the second candidate signature segment. For example, thesignature comparator 214 performs signature-by-signature matching of thefirst and second candidate signature segments. In examples disclosedherein, the signature comparator 214 compares the signatures of thefirst and second candidate signature segments at the starting point ofthe signature segment overlap. For example, the signature comparator 214identifies whether signatures of the second candidate signature segmentmatch the signature of first candidate signature segment at the startingpoint of the overlap. In some examples, the signature comparator 214identifies strong matches. As used herein, a strong match or strongsignature match refers to a difference between a first and secondsignature being less than a first deviation threshold. In examplesdisclosed herein, the first deviation threshold is one. For example, thesignature comparator 214 determines a strong signature match if a firstsignature is 33 and a second signature is 33 (e.g., the differencebetween the signatures is zero), if a first signature is 33 and a secondsignature is 34 (e.g., the difference between the signatures is one),etc. However, the first deviation threshold can be two, three, etc. Insome examples, the first deviation threshold varies (e.g., the signaturecomparator 214 determines the first deviation threshold).

In some examples, the signature comparator 214 analyzes ten signaturesof the second candidate signature segment for each signature of thefirst candidate signature segment to identify a strong match. If theexample signature comparator 214 does not identify a strong match fromten of the signatures of the second candidate signature segment, thesignature comparator 214 selects the subsequent signature of the firstcandidate signature segment. For example, if the signature comparator214 does not identify a strong match after analyzing ten of thesignatures of the second candidate signature segment compared to thefirst signature of the first candidate signature segment, the signaturecomparator 214 analyzes the second signature of the first candidatesignature segment. In some examples, the signature comparator analyzesmore than or less than ten signatures of the second candidate signaturesegment for each signature of the first candidate signature segment.

The example signature comparator 214 determines if there is a basicmatch between the first and second candidate signature segments. As usedherein, a basic match refers to a difference between a first and secondsignature being less than a second deviation threshold. In examplesdisclosed herein, the second deviation threshold is two. For example,the signature comparator 214 determines a basic signature match if afirst signature is 33 and a second signature is 33 (e.g., the differencebetween the signatures is zero), if a first signature is 33 and a secondsignature is 35 (e.g., the difference between the signatures is two),etc. However, the first deviation threshold can be three, four, etc. Insome examples, the second deviation threshold varies (e.g., thesignature comparator 214 determines the second deviation threshold). Inexamples disclosed herein, the second deviation threshold is greaterthan the first deviation threshold. That is, in examples disclosedherein, a strong match is also a basic match, but a basic match is notnecessarily a strong match. In some examples, the signature comparator214 determines if there are basic matches between the first and secondcandidate signature segments in response to the signature match counter216 determining the number of strong matches satisfies a first matchthreshold (described below). That is, the example signature comparator214 determines the first and second candidate signature segments includea match candidate in response to the number of strong matches satisfyingthe first match threshold.

The example signature comparator 214 determines whether candidatesignature segments match. That is, the example signature comparator 214determines whether the signature sequences of the overlap between firstand second candidate signature segments match (e.g., matching segment).In such examples, the signature comparator 214 determines the first andsecond candidate signature segments correspond to the same media asset.The example signature comparator 214 determines candidate signaturesegments match in response to the number of basic matches exceeding asecond match threshold. In examples disclosed herein, the second matchthreshold is 15. However, the second match threshold can be greater thanor less than 15. In some examples, the second match threshold varies(e.g., the signature comparator 214 determines the second matchthreshold).

The example signature match counter 216 of the illustrated example ofFIG. 2 obtains the output from the example signature comparator 214corresponding to a number, if any, of strong matches and/or basicmatches. For example, the signature comparator 214 provides informationindicative of the evaluation of the candidate signature segments to thesignature match counter 216. In examples disclosed herein, the examplesignature match counter 216 includes a counter, such as a device whichstores a number of times first and second candidate signature segmentscorrespond to a strong match. If the example signature match counter 216determines that strong matches were detected, the example signaturematch counter 216 increments the counter to the number of strong matchesthat were detected. For example, if the signature comparator 214detected four strong matches, the signature match counter 216 stores acount of four strong matches. If the example signature match counter 216does not receive information indicative of a detection of strongmatches, the example signature match counter 216 updates the strongmatch count with a count of zero.

Additionally or alternatively, the example signature match counter 216stores a number of times first and second candidate signature segmentscorrespond to a basic match. If the example signature match counter 216determines that basic matches were detected, the example signature matchcounter 216 increments the counter to the number of basic matches thatwere detected. For example, if the signature comparator 214 detected tenbasic matches, the signature match counter 216 stores a count of tenbasic matches. If the example signature match counter 216 does notreceive information indicative of a detection of basic matches, theexample signature match counter 216 updates the basic match count with acount of zero.

The example candidate stitcher 218 of the illustrated example of FIG. 2stitches candidate signature segments together. The example candidatestitcher 218 determines whether to stitch a first and a second candidatesignature segment together. For example, if the signature comparator 214determines the overlap between the first and second candidate signaturesegments match (e.g., the number of basic matches exceeds the secondmatch threshold), the candidate stitcher 218 stitches the first andsecond candidate signature segments together. If the example candidatestitcher 218 determines to stitch candidate signature segments together,the example candidate stitcher 218 determines a stitching point. Thatis, the example candidate stitcher 218 determines at what point in thefirst and second candidate signature segments to connect the firstcandidate signature segment to the second signature segment. In someexamples, the example candidate stitcher 218 determines the middle ofthe overlap between the first and second candidate signature segments isthe stitching point. However, the candidate stitcher 218 can determineany signature of the overlap is the stitching point (e.g., the firstsignature of the overlap, the last signature of the overlap, etc.). Theexample candidate stitcher 218 flags the selected signature as thestitching point.

The example candidate stitcher 218 discards signatures of the firstcandidate signature segment after the stitching point. The examplecandidate stitcher 218 inserts signatures from the second candidatesignature segment corresponding to the stitching point. That is, at thestitching point, the signatures of the second candidate signaturesegment replace the signatures of the first candidate signature segment.Thus, the example candidate stitcher 218 generates a stitched signature,including signatures of both the first and second candidate signaturesegments. The stitched signature corresponds to the same media asset asthe first and second candidate signature segments. The stitchedsignature has a longer time duration than both the first and secondcandidate signature segments. In some examples, the example candidatestitcher 218 stores the stitched signature in the reference signaturedatabase 220.

The reference signature database 220 of the illustrated example of FIG.2 stores signatures. For example, the reference signature database 220stores generated reference signatures created or otherwise obtained bythe data center 108. In some examples, the reference signature database220 includes reference unhashed signatures and/or referenced hashedsignatures. In some examples, the media monitoring entity associatedwith the reference signature database 220 can directly monitor mediasource feeds to generate reference unhashed signatures and/or hashedsignatures. In some examples, the media monitoring entity generatesreference unhashed signatures and/or hashed signatures from downloadedmedia (e.g., SVOD assets), etc. In examples disclosed herein, referencesignatures are generated using the same or similar techniques as themonitored media signatures, such that the monitored media signatures andreference signatures of the same asset match. In some examples, eachreference signature stored in the reference signature database 220 isassociated with a specific reference media asset, such as, but notlimited to, episodes of television programs (e.g., episodes of Game ofThrones, The Office, etc.), movies of a movie collection (e.g., TheMarvel Cinematic Universe, etc.), etc. In some examples, each referencesignature stored in the reference signature database 220 is associatedwith a timestamp, which indicates a position in the reference mediaasset represented by the reference signature. In some examples, thereference signature database 220 can include a library (e.g., database,table, etc.) of reference hashed signatures. Additionally oralternatively, the reference signature database 220 stores stitchedsignatures. For example, the reference signature database 220 storesstitched signatures generated by the candidate stitcher 218.

The example stitching validator 222 validates stitched signatures. Thatis, the example stitching validator 222 validates stitched signaturesgenerated by the example candidate stitcher 218. The example stitchingvalidator 222 obtains a reference signature from the example referencesignature database 220. In some examples, the reference signature is asignature sequence of the media asset created or otherwise obtained bythe data center 108 based on a continuous viewing of the media asset.The example stitching validator 222 identifies the stitching point inthe stitched signature. For example, the stitching validator 222identifies the stitching point based on the flag set by the candidatestitcher 218. The example stitching validator 222 compares the stitchedsignature to the reference signature at the stitching point.

In examples disclosed herein, the stitching validator 222 determines avalidation start point and a validation end point in the stitchedsignature (e.g., a validation segment). That is, the stitching validator222 determines a validation segment in the stitched signature. Forexample, the validation start point can be a time duration before thestitching point and the validation end point can be a time durationafter the stitching point. In some examples, the time duration is 10seconds. That is, the example stitching validator 222 determines thevalidation start point is 10 seconds before the stitching point and thevalidation end point is 10 seconds after the stitching point. However,the time duration can be greater or less than 10 seconds. For example,the validation start point can be eight seconds before the stitchingpoint, the validation end point can be 12 seconds after the stitchingpoint, etc.

Thus, the example stitching validator 222 performssignature-by-signature matching between the stitched signature and thereference signature. The example stitching validator 222 determines ifthere are mismatches between the stitched signature and the referencesignature. For example, the stitching validator 222 counts the number ofcontinuous basic matches between the stitched signature and thereference signature. In some examples, the stitching validator 222identifies a mismatch between signatures of the stitched signature andthe reference signature. That is, a signature of the stitched signatureand a signature of the reference signature are not within the seconddeviation threshold (e.g., are not a basic match). In such examples, thestitching validator 222 determines a count of mismatches between thestitched signature and the reference signature.

The example stitching validator 222 determines if the stitched signatureis validated. For example, the stitching validator 222 determines thestitched signature is validated if the number of mismatches does notexceed a mismatch threshold. The mismatch threshold can be one. However,the mismatch threshold can be greater than one (e.g., two, three, etc.).For example, if the mismatch threshold is one, and the stitchingvalidator 222 counted zero mismatches between the stitched signature andthe reference signature, the stitching validator 222 validates thestitched signature. That is, the stitching validator 222 determines thestitched signature can be used for future crediting of the media assetand/or previous crediting is accurate (e.g., media exposures credited tothe stitched signature before the corresponding reference signature wasgenerated are correct).

In some examples, the stitching validator 222 determines the stitchedsignature is not accurate (e.g., the number of mismatches is greaterthan the mismatch threshold). For example, the stitched signature may bemissing signatures compared to the reference signature, the stitchedsignature may have additional signatures compared to the referencesignature, etc. In some examples, the stitching validator 222 flags thestitched signature for manual inspection by an analyst. For example, theanalyst may determine the mismatches identified by the stitchingvalidator 222 are normal PAS behavior.

FIG. 3 is an example illustration of an example first candidatesignature segment 300 and an example second candidate signature segment350. The first candidate signature segment 300 includes timestamps 302and signatures 304 and the second candidate signature segment 350includes timestamps 352 and signatures 354. In the illustrated exampleof FIG. 3 , the timing handler 210 (FIG. 2 ) aligns the candidatesignature segments 300, 350 based on the timestamps 302, 352. Forexample, the signature 306 of the first candidate signature segment 300and the signature 308 of the second candidate signature segment 350 bothcorrespond to the time 2,000. However, the first signature 306 is 15 andthe second signature 308 is 33. Thus, the example signature comparator214 (FIG. 2 ) determines the signatures 306, 308 do not match (e.g., thedifference between the signatures 306, 308 exceeds the second deviationthreshold and, thus, is not a basic match or a strong match).

In the illustrated example of FIG. 3 , the signature comparator 214identifies an example first strong match 310 (e.g., between the fourthsignature of the first candidate signature segment 300 and the firstsignature of the second candidate signature segment 350), an examplesecond strong match 312 (e.g., between the fifth signature of the firstcandidate signature segment 300 and the second signature of the secondcandidate signature segment 350), an example third strong match 314(e.g., between the sixth signature of the first candidate signaturesegment 300 and the third signature of the second candidate signaturesegment 350), and an example fourth strong match 316 (e.g., between theseventh signature of the first candidate signature segment 300 and thefourth signature of the second candidate signature segment 350). Thus,the signature match counter 216 determines there are four consecutivestrong matches between the candidate signature segments 300, 350.

Additionally or alternatively, the signature comparator 214 identifiesan example fifth strong match 318 (e.g., between the twenty-fifthsignature of the first candidate signature segment 300 and thetwenty-second signature of the second candidate signature segment 350),an example sixth strong match 320 (e.g., between the twenty-fourthsignature of the first candidate signature segment 300 and thetwenty-first signature of the second candidate signature segment 350),an example seventh strong match 322 (e.g., between the twenty-thirdsignature of the first candidate signature segment 300 and the twentiethsignature of the second candidate signature segment 350), and an exampleeighth strong match 324 (e.g., between the twenty-second signature ofthe first candidate signature segment 300 and the nineteenth signatureof the second candidate signature segment 350). Thus, the signaturematch counter 216 determines there are an additional four consecutivestrong matches between the candidate signature segments 300, 350.

FIG. 4 is an example illustration of an example first candidatesignature segment 400 and an example second candidate signature segment450 that overlap. The first candidate signature segment 400 includestimestamps 402 and signatures 404 and the second candidate signaturesegment 450 includes timestamps 452 and signatures 454. The examplesignature comparator 214 (FIG. 2 ) identifies a first match candidate406. That is, the example signature comparator 214 identified fourstrong matches between the candidate signature segments 400, 450. Thus,in response to the number of strong matches satisfying the first matchthreshold, the example signature comparator 214 determines to identifybasic matches. However, the example signature matcher 212 (FIG. 2 )discards the first match candidate 406 because the next signatures ofthe candidate signature segments 400, 450 are not basic matches (e.g.,the difference between 56 and 52 is not within the second deviationthreshold).

The example signature comparator 214 identifies a second match candidate408. That is, the signature comparator 214 identified four continuousstrong matches in the second match candidate 408. The number of strongmatches satisfies the first match threshold of 4. Thus, the examplesignature comparator 214 determines basic matches. In some examples, thefirst match threshold varies (e.g., the signature comparator 214determines the first match threshold). In the illustrated example ofFIG. 4 , the signature comparator 214 identified an example overlap 410.That is, the signature comparator 214 identified 30 continuous basicmatches between the candidate signature segments 400, 450. In someexamples, the signature match counter 216 stores the number of strongmatches and/or basic matches.

In the illustrated example of FIG. 4 , the number of basic matchessatisfies the second match threshold of 15. Thus, the candidate stitcher218 (FIG. 2 ) determines to stitch the candidate signature segments 400,450 together. The candidate stitcher 218 determines an example stitchingpoint 412. The example stitching point 412 is part of the overlap 410.The example candidate stitcher 418 discards the example signatures 414of the first candidate signature segment 400. That is, the examplesignatures 414 of the example first candidate signature segment 400 areafter the example stitching point 412. The example second candidatesignature segment 450 includes example signatures 416 after thestitching point 412. In examples disclosed herein, the candidatestitcher 418 replaces the signatures 414 of the first candidatesignature segment 400 with the signatures 416 of the second candidatesignature segment 450.

FIG. 5 is an example illustration of an example stitched signature 500generated in accordance with teachings of this disclosure based on thefirst candidate signature segment 400 and the second candidate signaturesegment 450 of FIG. 4 . The example stitched signature 500 includesexample signatures 502. The example signatures 502 correspond to thefirst candidate signature segment 400. The example signatures 502include the example stitching point 412 (FIG. 4 ). The stitchedsignature 500 includes example signatures 504. The example signatures504 correspond to the second candidate signature segment 450 (e.g., thesignatures 416 (FIG. 4 )).

The example timing handler 210 (FIG. 2 ) updates example timestamps 506corresponding to the signatures 504. That is, the example candidatestitcher 218 does not use the timestamps 452 (FIG. 4 ) of the signatures416. Instead, the timing handler 210 determines timestamps 506 based onexample timestamps 508 corresponding to the first candidate signaturesegment 400 for logical consistency.

FIG. 6 . is an example illustration of an example reference signature600 and an example stitched signature 650 that is validated. The examplestitching validator 222 (FIG. 2 ) identifies the example stitching point602. The example stitching validator 222 identifies an examplevalidation start point 604 and an example validation end point 606. Forexample, the validation start point 604 is 12 signatures before thestitching point 602 and the validation end point 606 is 17 signaturesafter the stitching point 602. The example stitching validator 222performs signature-by-signature matching starting at the validationstart point 604 and the validation end point 606.

In the illustrated example of FIG. 6 , there is example normal PASbehavior 608. The example normal PAS behavior 608 includes twosignatures. The two signatures of the normal PAS behavior 608 do notcorrespond to a strong or basic match with respect to the referencesignature. However, the normal PAS behavior 608 is not a mismatch and,thus, the stitched signature 650 is validated.

FIG. 7 is an example illustration of an example reference signature 700and an example stitched signature 750 that is not validated. The examplereference signature 700 includes example signatures 702. The examplestitched signature 750 is missing the signatures 702. Thus, thestitching validator 222 (FIG. 2 ) determines a mismatch count of two.The stitching validator 222 determines the mismatch count is greaterthan the mismatch threshold and, thus, the stitched signature 750 is notvalidated. In some examples, the stitching validator 222 flags thestitched signature 750 for further inspection.

While an example manner of implementing the meter data analyzer 110 ofFIG. 1 is illustrated in FIG. 2 , one or more of the elements, processesand/or devices illustrated in FIG. 2 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example network interface 202, the example buffer 204, theexample signature handler 206, the example candidate checker 208, theexample timing handler 210, the example signature matcher 212, theexample signature comparator 214, the example signature match counter216, the example candidate stitcher 218, the example reference signaturedatabase 220, the example stitching validator 222, and/or, moregenerally, the example meter data analyzer 110 of FIG. 2 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample network interface 202, the example buffer 204, the examplesignature handler 206, the example candidate checker 208, the exampletiming handler 210, the example signature matcher 212, the examplesignature comparator 214, the example signature match counter 216, theexample candidate stitcher 218, the example reference signature database220, the example stitching validator 222 and/or, more generally, theexample meter data analyzer 110 could be implemented by one or moreanalog or digital circuit(s), logic circuits, programmable processor(s),programmable controller(s), graphics processing unit(s) (GPU(s)),digital signal processor(s) (DSP(s)), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example, networkinterface 202, the example buffer 204, the example signature handler206, the example candidate checker 208, the example timing handler 210,the example signature matcher 212, the example signature comparator 214,the example signature match counter 216, the example candidate stitcher218, the example reference signature database 220, and/or the examplestitching validator 222 is/are hereby expressly defined to include anon-transitory computer readable storage device or storage disk such asa memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-raydisk, etc. including the software and/or firmware. Further still, theexample meter data analyzer 110 of FIG. 1 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 2 , and/or may include more than one of any or allof the illustrated elements, processes and devices. As used herein, thephrase “in communication,” including variations thereof, encompassesdirect communication and/or indirect communication through one or moreintermediary components, and does not require direct physical (e.g.,wired) communication and/or constant communication, but ratheradditionally includes selective communication at periodic intervals,scheduled intervals, aperiodic intervals, and/or one-time events.

Flowcharts representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the meter data analyzer 110 ofFIGS. 1 and/or 2 are shown in FIGS. 8-11 . The machine readableinstructions may be one or more executable programs or portion(s) of anexecutable program for execution by a computer processor and/orprocessor circuitry, such as the processor 1212 shown in the exampleprocessor platform 1200 discussed below in connection with FIG. 12 . Theprogram may be embodied in software stored on a non-transitory computerreadable storage medium such as a CD-ROM, a floppy disk, a hard drive, aDVD, a Blu-ray disk, or a memory associated with the processor 1212, butthe entire program and/or parts thereof could alternatively be executedby a device other than the processor 1212 and/or embodied in firmware ordedicated hardware. Further, although the example program is describedwith reference to the flowcharts illustrated in FIGS. 8-11 , many othermethods of implementing the example meter data analyzer 110 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined. Additionally or alternatively, any or all ofthe blocks may be implemented by one or more hardware circuits (e.g.,discrete and/or integrated analog and/or digital circuitry, an FPGA, anASIC, a comparator, an operational-amplifier (op-amp), a logic circuit,etc.) structured to perform the corresponding operation withoutexecuting software or firmware. The processor circuitry may bedistributed in different network locations and/or local to one or moredevices (e.g., a multi-core processor in a single machine, multipleprocessors distributed across a server rack, etc.).

The machine readable instructions described herein may be stored in oneor more of a compressed format, an encrypted format, a fragmentedformat, a compiled format, an executable format, a packaged format, etc.Machine readable instructions as described herein may be stored as dataor a data structure (e.g., portions of instructions, code,representations of code, etc.) that may be utilized to create,manufacture, and/or produce machine executable instructions. Forexample, the machine readable instructions may be fragmented and storedon one or more storage devices and/or computing devices (e.g., servers)located at the same or different locations of a network or collection ofnetworks (e.g., in the cloud, in edge devices, etc.). The machinereadable instructions may require one or more of installation,modification, adaptation, updating, combining, supplementing,configuring, decryption, decompression, unpacking, distribution,reassignment, compilation, etc. in order to make them directly readable,interpretable, and/or executable by a computing device and/or othermachine. For example, the machine readable instructions may be stored inmultiple parts, which are individually compressed, encrypted, and storedon separate computing devices, wherein the parts when decrypted,decompressed, and combined form a set of executable instructions thatimplement one or more functions that may together form a program such asthat described herein.

In another example, the machine readable instructions may be stored in astate in which they may be read by processor circuitry, but requireaddition of a library (e.g., a dynamic link library (DLL)), a softwaredevelopment kit (SDK), an application programming interface (API), etc.in order to execute the instructions on a particular computing device orother device. In another example, the machine readable instructions mayneed to be configured (e.g., settings stored, data input, networkaddresses recorded, etc.) before the machine readable instructionsand/or the corresponding program(s) can be executed in whole or in part.Thus, machine readable media, as used herein, may include machinereadable instructions and/or program(s) regardless of the particularformat or state of the machine readable instructions and/or program(s)when stored or otherwise at rest or in transit.

The machine readable instructions described herein can be represented byany past, present, or future instruction language, scripting language,programming language, etc. For example, the machine readableinstructions may be represented using any of the following languages: C,C++, Java, C #, Perl, Python, JavaScript, HyperText Markup Language(HTML), Structured Query Language (SQL), Swift, etc.

As mentioned above, the example processes of FIGS. 8-11 may beimplemented using executable instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim employs any formof “include” or “comprise” (e.g., comprises, includes, comprising,including, having, etc.) as a preamble or within a claim recitation ofany kind, it is to be understood that additional elements, terms, etc.may be present without falling outside the scope of the correspondingclaim or recitation. As used herein, when the phrase “at least” is usedas the transition term in, for example, a preamble of a claim, it isopen-ended in the same manner as the term “comprising” and “including”are open ended. The term “and/or” when used, for example, in a form suchas A, B, and/or C refers to any combination or subset of A, B, C such as(1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) Bwith C, and (7) A with B and with C. As used herein in the context ofdescribing structures, components, items, objects and/or things, thephrase “at least one of A and B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. Similarly, as used herein in the contextof describing structures, components, items, objects and/or things, thephrase “at least one of A or B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. As used herein in the context ofdescribing the performance or execution of processes, instructions,actions, activities and/or steps, the phrase “at least one of A and B”is intended to refer to implementations including any of (1) at leastone A, (2) at least one B, and (3) at least one A and at least one B.Similarly, as used herein in the context of describing the performanceor execution of processes, instructions, actions, activities and/orsteps, the phrase “at least one of A or B” is intended to refer toimplementations including any of (1) at least one A, (2) at least one B,and (3) at least one A and at least one B.

As used herein, singular references (e.g., “a”, “an”, “first”, “second”,etc.) do not exclude a plurality. The term “a” or “an” entity, as usedherein, refers to one or more of that entity. The terms “a” (or “an”),“one or more”, and “at least one” can be used interchangeably herein.Furthermore, although individually listed, a plurality of means,elements or method actions may be implemented by, e.g., a single unit orprocessor. Additionally, although individual features may be included indifferent examples or claims, these may possibly be combined, and theinclusion in different examples or claims does not imply that acombination of features is not feasible and/or advantageous.

FIG. 8 is a flowchart representative of machine-readable instructionswhich may be executed to implement the example meter data analyzer 110of FIGS. 1 and/or 2 to perform signature stitching. The example process800 of the illustrated example of FIG. 8 begins when the example networkinterface 202 (FIG. 2 ) obtains a first signature segment and a secondsignature segment (block 802). For example, the network interface 202receives monitoring data 104A, 104B, 104C from the example network 106.In some examples, the network interface 202 can convert the receivedmonitoring data 104A, 104B, 104C into a format readable by the meterdata analyzer 110.

The example candidate checker 208 (FIG. 2 ) determines if the firstsignature segment or the second signature segment are stored in theexample reference signature database 220 (FIG. 2 ) (block 804). Forexample, the candidate checker 208 compares the first and secondsignature segments in the monitoring data 104A, 104B, 104C to thereference signatures stored in the reference signature database 220. Insome examples, the candidate checker 208 uses unhashed (e.g., linear)signature matching. In some examples, the candidate checker 208 useshashed signature matching. If the example candidate checker 208determines the first signature segment or the second signature segmentis in the example reference signature database 220, control proceeds toblock 820.

If the example candidate checker 208 determines the first signaturesegment and the second signature segment are not in the referencesignature database 220, the example candidate checker 208 determines ifthe first and second signature segments meet candidate criteria (block806). For example, the candidate checker 208 determines the timeduration of the first signature segment and the time duration of thesecond signature segment. The example candidate checker 208 compares thetime durations of the first and second signature segments to a candidateduration threshold. In some examples, the candidate duration thresholdis 60 seconds. If the candidate checker 208 determines the first orsecond signature segments do not exceed the candidate durationthreshold, control proceeds to block 820.

If, at block 806, the candidate checker 208 determines the timedurations of the first and second signature segments exceed thecandidate duration threshold, the candidate checker 208 flags the firstand second signature segments as candidate signature segments and theexample timing handler 210 (FIG. 2 ) aligns the first and secondcandidate signature segments based on timestamps of the first and secondsignature segments (block 808). For example, the timing handler 210compares the timestamps of the first and second candidate signaturesegments. The timing handler 210 determines an alignment point in thefirst and second candidate signature segments.

The example signature matcher 212 (FIG. 2 ) performssignature-by-signature matching (block 810). For example, the signaturematcher 212 compares the first candidate signature segment to the secondcandidate signature segment at the alignment point. The examplesignature matcher 212 determines whether the overlap between the firstand second candidate signature segments match. An example implementationof the signature-by-signature matching process 810 of FIG. 8 isdescribed in further detail in connection with FIG. 9 .

The example candidate stitcher 218 (FIG. 2 ) determines whether tostitch the first candidate signature segment and the second candidatesignature segment together (block 812). For example, the candidatestitcher 218 determines if the first and second candidate signaturesegments match based on the determination of the example signaturematcher 212. If the example candidate stitcher 218 determines to notstitch the first and second candidate signature segments together,control proceeds to block 820. If the example candidate stitcher 218determines to stitch the first and second candidate signature segmentstogether, the example candidate stitcher 218 stitches the first andsecond candidate signature segments (block 814). An exampleimplementation of the stitching process 814 of FIG. 8 is described infurther detail in connection with FIG. 10 .

The example stitching validator 222 (FIG. 2 ) determines whether tovalidate the stitched signature (block 816). For example, the stitchingvalidator 222 may determine whether a reference signature is stored inthe reference signature database 220 and, if so, determine to validatethe stitched signature. If the stitching validator 222 determines to notvalidate the stitched signature, control proceeds to block 820. If thestitching validator 222 determines to validate the stitched signature,the stitching validator 222 compares the stitched signature to areference signature to validate the stitched signature (block 816). Forexample, the stitching validator 222 performs signature-by-signaturematching between the stitched signature and the reference signature. Anexample implementation of the validation process 818 of FIG. 8 isdescribed in further detail in connection with FIG. 11 .

The meter data analyzer 110 determines whether to analyze additionalsignatures (block 820). For example, if the network interface 202obtains additional signature segments, the meter data analyzer 110 maydetermine to analyze the additional signature segments. If, at block820, the meter data analyzer 110 determines to analyze additionalsignature segments, the program 800 returns to block 802. Otherwise, theprogram 800 ends.

FIG. 9 is a flowchart representative of machine-readable instructionswhich may be executed to implement the example signature matcher 212 ofFIG. 2 to perform signature-by-signature matching. The example candidatechecker 208 (FIG. 2 ) determines a number of strong matches between thefirst and second candidate signature segments (block 902). For example,the candidate checker 208 compares signatures of the first and secondcandidate signature segments using a first deviation threshold. In someexamples, the first deviation threshold is one. The example signaturematch counter 216 (FIG. 2 ) increments a strong match count if thesignatures of the first and second candidate signature segments do notexceed the first deviation threshold.

The example candidate checker 208 determines if the number of continuousstrong signature matches exceeds a first match threshold (block 904).For example, the candidate checker 208 compares the strong match countdetermined by the signature match counter 216 to the first matchthreshold. In some examples, the first match threshold is four. If theexample candidate checker 208 determines the number of continuous strongmatches does not exceed the first match threshold, control proceeds toblock 912.

If, at block 904, the example candidate checker 208 determines thenumber of continuous strong signature matches does exceed the firstmatch threshold, the example signature handler 206 determines a numberof basic matches between the first and second candidate signaturesegments (block 906). For example, the candidate checker 208 comparesthe signatures of the first and second candidate signature segmentsusing a second deviation threshold. That is, the candidate checker 208determines whether a signature of the first candidate signature segmentand a signature of the second candidate signature segment are a basicmatch if the difference between the signatures is less than the seconddeviation threshold. In some examples, the second deviation threshold istwo. The example signature match counter 216 increments a basicsignature match if the candidate checker 208 determines the signaturesof the first and second candidate signature segments are a basic match.

The example signature matcher 212 determines if the number of continuousbasic signature matches exceeds a second match threshold (block 908).For example, the candidate checker 208 compares the number of basicsignature matches determined by the signature match counter 216 to thesecond match threshold. In some examples, the second match threshold is15. If the signature matcher 212 determines the number of continuousbasic signature matches exceeds the second threshold, the candidatechecker 208 indicates the first and second candidate signature segmentsinclude a match (block 910). That is, the first candidate signaturesegment includes signatures that match (e.g., strong match, basic match,etc.) the second candidate signature segment (e.g., a matching segment).

Returning to block 908, if the example signature matcher 212 determinesthe number of continuous basic signature matches do not exceed thesecond match threshold, the signature handler 206 determines whether tocontinue analyzing the first and second candidate signature segments(block 912). For example, the signature handler 206 may determine tocontinue analyzing the first and second candidate signature segments ifthe first candidate signature segment includes signatures that have notbeen analyzed. If the signature handler 206 determines to continueanalyzing the first and second candidate signature segments, controlreturns to block 902. If the example signature handler 206 determines tonot continue analyzing the first and second candidate signaturesegments, the example signature handler 206 indicates the first andsecond candidate signature segments do not include a match (block 914).That is, the first candidate signature segment does not include a numberof continuous signatures that match (e.g., strong match, basic match,etc.) the second candidate signature segment. The example meter dataanalyzer 110 (FIG. 1 ) returns to block 812 of process 800 of FIG. 8 .

FIG. 10 is a flowchart representative of machine-readable instructionswhich may be executed to implement an example candidate stitcher 218 ofFIG. 2 to stitch candidate signature segments together. The examplecandidate stitcher 218 determines a stitching point (block 1002). Forexample, the candidate stitcher 218 determines a signature in thematching segment of the first and second candidate signature segments tobe the stitching point. In some examples, the candidate stitcher 218determines the middle signature of the matching segment is the stitchingpoint, the first signature of the matching segment is the stitchingpoint, the last signature of the matching segment is the stitchingpoint, etc.

The example candidate stitcher 218 discards data from the firstcandidate signature segment after the stitching point (block 1004). Forexample, the candidate stitcher 218 removes the timestamps and thesignatures of the first candidate signature segment after the stitchingpoint. The example candidate stitcher 218 inserts data from the secondcandidate signature segment after the stitching point to the firstcandidate signature segment (block 1006). For example, the candidatestitcher 218 inserts the timestamps and the signatures of the secondcandidate signature segment after the stitching point to the signaturesof the first candidate signature segment. That is, the candidatestitcher 218 generates a stitched signature.

The example timing handler 210 (FIG. 2 ) recalculates the timestamps ofthe second candidate signature segment based on the timestamps of thefirst candidate signature segment of the stitched signature (block1008). For example, the timing handler 210 determines timestamps of thesignatures of the second candidate signature segment after the stitchingpoint based on the timestamps of the signatures of the first candidatesignature segment. In some examples, the candidate stitcher 218 storesthe stitched signature in the reference signature database 220 (FIG. 2). The example meter data analyzer 110 (FIG. 1 ) returns to block 816 ofprocess 800 of FIG. 8 .

FIG. 11 is a flowchart representative of machine-readable instructionswhich may be executed to implement the example stitching validator 222of FIG. 2 to validate stitched signatures. The example stitchingvalidator 222 obtains a reference signature and a stitched signature(block 1102). For example, the stitching validator 222 obtains thereference signature and the stitched signature from the referencesignature database 220 (FIG. 2 ). The example stitching validator 222identifies the stitching point in the stitched signature (block 1104).For example, the stitching validator 222 identifies the flag set by thecandidate stitcher 218 (FIG. 2 ) corresponding to the signature of thestitching point.

The example stitching validator 222 determines a validation segment(block 1106). For example, the stitching validator 222 determines avalidation start point and a validation end point in the stitchedsignature. In some examples, the stitching validator 222 determines thevalidation start point is a time duration before the stitching point andthe validation end point is a time duration after the stitching point.In some examples, the time duration is ten seconds. In some examples,the validation segment is the sequence of signatures between thevalidation start point and the validation end point.

The example stitching validator 222 determines a number of mismatchesbetween the stitched signature and the reference signature in thevalidation segment (block 1108). For example, the stitching validator222 compares the signatures of the stitched signature to the signaturesof the reference signature. In some examples, if the difference betweenthe signatures of the stitched signature and the reference signature aregreater than the first deviation threshold corresponding to a strongmatch, the stitching validator 222 determines a mismatch.

The example stitching validator 222 updates the mismatch count (block1110). For example, if the stitching validator 222 identified twomismatches between the stitched signature and the reference signature,the stitching validator 222 updates the mismatch count to twomismatches. The example stitching validator 222 determines if the numberof mismatches exceeds a mismatch threshold. For example, the stitchingvalidator 222 compares the number of mismatches to the mismatchthreshold. In some examples, the mismatch threshold is one. If theexample stitching validator 222 determines the number of mismatches doesnot exceed the mismatch threshold, the example stitching validator 222indicates the stitched signature is validated (block 1114). For example,the stitching validator 222 can flag the stitched signature asvalidated.

Returning to block 1112, if the example stitching validator 222determines the number of mismatches exceeds the mismatch threshold, thestitching validator 222 indicates the stitched signature is notvalidated (block 1116). For example, the stitching validator 222 flagsthe stitched signature as not validated. In some examples, the flag thatthe stitched signature is not validated indicates the stitched signaturerequires further inspection. The example meter data analyzer 110 (FIG. 1) returns to block 820 of process 800 of FIG. 8 .

FIG. 12 is a block diagram of an example processor platform 1200structured to execute the instructions of FIGS. 8-11 to implement themeter data analyzer 110 of FIGS. 1 and/or 2 . The processor platform1200 can be, for example, a server, a personal computer, a workstation,a self-learning machine (e.g., a neural network), a mobile device (e.g.,a cell phone, a smart phone, a tablet such as an iPad™), a personaldigital assistant (PDA), an Internet appliance, a DVD player, a CDplayer, a digital video recorder, a Blu-ray player, a gaming console, apersonal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 1200 of the illustrated example includes aprocessor 1212. The processor 1212 of the illustrated example ishardware. For example, the processor 1212 can be implemented by one ormore integrated circuits, logic circuits, microprocessors, GPUs, DSPs,or controllers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example signature handler206, the example candidate checker 208, the example timing handler 210,the example signature matcher 212, the example signature comparator 214,the example signature match counter 216, the example candidate stitcher218, and the example stitching validator 222.

The processor 1212 of the illustrated example includes a local memory1213 (e.g., a cache). The processor 1212 of the illustrated example isin communication with a main memory including a volatile memory 1214 anda non-volatile memory 1216 via a bus 1218. The volatile memory 1214 maybe implemented by Synchronous Dynamic Random Access Memory (SDRAM),Dynamic Random Access Memory (DRAM), RAMBUS® Dynamic Random AccessMemory (RDRAM®) and/or any other type of random access memory device.The non-volatile memory 1216 may be implemented by flash memory and/orany other desired type of memory device. Access to the main memory 1214,1216 is controlled by a memory controller.

The processor platform 1200 of the illustrated example also includes aninterface circuit 1220. The interface circuit 1220 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 1222 are connectedto the interface circuit 1220. The input device(s) 1222 permit(s) a userto enter data and/or commands into the processor 1212. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 1224 are also connected to the interfacecircuit 1220 of the illustrated example. The output devices 1224 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 1220 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 1220 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 1226. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 1200 of the illustrated example also includes oneor more mass storage devices 1228 for storing software and/or data.Examples of such mass storage devices 1228 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives.

The machine executable instructions 1232 of FIGS. 8-11 may be stored inthe mass storage device 1228, in the volatile memory 1214, in thenon-volatile memory 1216, and/or on a removable non-transitory computerreadable storage medium such as a CD or DVD.

A block diagram illustrating an example software distribution platform1305 to distribute software such as the example computer readableinstructions 1232 of FIG. 12 to third parties is illustrated in FIG. 13. The example software distribution platform 1305 may be implemented byany computer server, data facility, cloud service, etc., capable ofstoring and transmitting software to other computing devices. The thirdparties may be customers of the entity owning and/or operating thesoftware distribution platform. For example, the entity that owns and/oroperates the software distribution platform may be a developer, aseller, and/or a licensor of software such as the example computerreadable instructions 1232 of FIG. 12 . The third parties may beconsumers, users, retailers, OEMs, etc., who purchase and/or license thesoftware for use and/or re-sale and/or sub-licensing. In the illustratedexample, the software distribution platform 1305 includes one or moreservers and one or more storage devices. The storage devices store thecomputer readable instructions 1232, which may correspond to the examplecomputer readable instructions 1232 of FIGS. 8-11 , as described above.The one or more servers of the example software distribution platform1305 are in communication with a network 1310, which may correspond toany one or more of the Internet and/or any of the example networks 106,1226 described above. In some examples, the one or more servers areresponsive to requests to transmit the software to a requesting party aspart of a commercial transaction. Payment for the delivery, sale and/orlicense of the software may be handled by the one or more servers of thesoftware distribution platform and/or via a third party payment entity.The servers enable purchasers and/or licensors to download the computerreadable instructions 1232 from the software distribution platform 1305.For example, the software, which may correspond to the example computerreadable instructions 1232 of FIG. 12 , may be downloaded to the exampleprocessor platform 1200, which is to execute the computer readableinstructions 1232 to implement the meter data analyzer 110. In someexample, one or more servers of the software distribution platform 1305periodically offer, transmit, and/or force updates to the software(e.g., the example computer readable instructions 1232 of FIG. 12 ) toensure improvements, patches, updates, etc. are distributed and appliedto the software at the end user devices.

From the foregoing, it will be appreciated that example methods,apparatus and articles of manufacture have been disclosed that generatesignatures of media based on signature segments corresponding tointerrupted exposure data. For example, the methods, apparatus andarticles of manufacture disclosed herein determine an overlap ofmatching signatures between one or more signature segments that do notcorrespond to the entirety of the media asset. The signature segmentsare then stitched together to form a signature corresponding to a longertime duration of the media asset. In some examples, the signaturesegments are analyzed and stitched together if the duration of thesignature segment exceeds a threshold. The disclosed methods, apparatusand articles of manufacture improve the efficiency of using a computingdevice by determining whether signature segments have a time durationexceeding a threshold before analyzing and stitching signaturestogether. The disclosed methods, apparatus and articles of manufactureare accordingly directed to one or more improvement(s) in thefunctioning of a computer.

Example methods, apparatus, systems, and articles of manufacture togenerate a signature based on signature candidates are disclosed herein.Further examples and combinations thereof include the following:

Example 1 includes an apparatus, comprising a timing handler todetermine an alignment point of a first candidate signature segment anda second candidate signature segment, the first candidate signaturesegment and the second candidate signature segment including time dataand signature data, the alignment point based on the time data of thefirst candidate signature segment and the time data of the secondcandidate signature segment, a signature comparator to compare a firstsignature to a second signature at the alignment point, the firstsignature included in the first candidate signature segment and thesecond signature included in the second candidate signature segment, anda candidate stitcher to stitch the second signature to the firstsignature based on the comparison to generate a stitched signature, thestitched signature used for media crediting.

Example 2 includes the apparatus of example 1, further including acandidate checker to determine whether the first candidate signaturesegment and the second candidate signature segment meet a candidateduration threshold.

Example 3 includes the apparatus of example 2, wherein the candidatechecker is to determine the candidate duration threshold based on atleast one of validation data or a stitching ability.

Example 4 includes the apparatus of example 1, wherein the signaturecomparator is to determine a strong match between the first candidatesignature segment and the second candidate signature segment in responseto a difference between the first signature and the second signaturebeing less than a first deviation threshold.

Example 5 includes the apparatus of example 4, wherein the firstdeviation threshold is one.

Example 6 includes the apparatus of example 1, further including asignature match counter to count a number of strong matches between thefirst candidate signature segment and the second candidate signaturesegment.

Example 7 includes the apparatus of example 6, wherein the signaturecomparator is to identify a basic match between the first candidatesignature segment and the second candidate signature segment in responseto the number of strong matches exceeding a first match threshold.

Example 8 includes the apparatus of example 7, wherein the first matchthreshold is four.

Example 9 includes the apparatus of example 7, wherein the signaturecomparator is to determine the basic match in response to a differencebetween the first signature and the second signature being less than asecond deviation threshold.

Example 10 includes the apparatus of example 9, wherein the seconddeviation threshold is two.

Example 11 includes the apparatus of example 6, wherein the signaturematch counter is to count a number of basic matches between the firstcandidate signature segment and the second candidate signature segment.

Example 12 includes the apparatus of example 11, wherein the candidatestitcher is to stitch the second candidate signature segment to thefirst candidate signature segment to generate a stitched signature inresponse to the number of basic matches exceeding a second matchthreshold.

Example 13 includes the apparatus of example 12, wherein the secondmatch threshold is 15.

Example 14 includes the apparatus of example 1, wherein the timinghandler is to determine a timestamp for the second signature of thestitched signature based on the time data of the signatures of the firstcandidate.

Example 15 includes at least one non-transitory computer readable mediumcomprising instructions that, when executed, cause at least oneprocessor to at least determine an alignment point of a first candidatesignature segment and a second candidate signature segment, the firstcandidate signature segment and the second candidate signature segmentincluding time data and signature data, the alignment point based on thetime data of the first candidate signature segment and the time data ofthe second candidate signature segment, compare a first signature to asecond signature at the alignment point, the first signature included inthe first candidate signature segment and the second signature includedin the second candidate signature segment, and stitch the secondsignature to the first signature based on the comparison to generate astitched signature, the stitched signature used for media crediting.

Example 16 includes the at least one non-transitory computer readablemedium of example 15, wherein the instructions, when executed, cause theat least one processor to determine whether the first candidatesignature segment and the second candidate signature segment meet acandidate duration threshold.

Example 17 includes the at least one non-transitory computer readablemedium of example 16, wherein the instructions, when executed, cause theat least one processor to determine the candidate duration thresholdbased on at least one of validation data or a stitching ability.

Example 18 includes the at least one non-transitory computer readablemedium of example 15, wherein the instructions, when executed, cause theat least one processor to determine a strong match between the firstcandidate signature segment and the second candidate signature segmentin response to a difference between the first signature and the secondsignature being less than a first deviation threshold.

Example 19 includes the at least one non-transitory computer readablemedium of example 18, wherein the first deviation threshold is one.

Example 20 includes the at least one non-transitory computer readablemedium of example 15, wherein the instructions, when executed, cause theat least one processor to count a number of strong matches between thefirst candidate signature segment and the second candidate signaturesegment.

Example 21 includes the at least one non-transitory computer readablemedium of example 20, wherein the instructions, when executed, cause theat least one processor to identify a basic match between the firstcandidate signature segment and the second candidate signature segmentin response to the number of strong matches exceeding a first matchthreshold.

Example 22 includes the at least one non-transitory computer readablemedium of example 21, wherein the first match threshold is four.

Example 23 includes the at least one non-transitory computer readablemedium of example 21, wherein the instructions, when executed, cause theat least one processor to determine the basic match in response to adifference between the first signature and the second signature beingless than a second deviation threshold.

Example 24 includes the at least one non-transitory computer readablemedium of example 23, wherein the second deviation threshold is two.

Example 25 includes the at least one non-transitory computer readablemedium of example 20, wherein the instructions, when executed, cause theat least one processor to count a number of basic matches between thefirst candidate signature segment and the second candidate signaturesegment.

Example 26 includes the at least one non-transitory computer readablemedium of example 25, wherein the instructions, when executed, cause theat least one processor to stitch the second candidate signature segmentto the first candidate signature segment to generate a stitchedsignature in response to the number of basic matches exceeding a secondmatch threshold.

Example 27 includes the at least one non-transitory computer readablemedium of example 26, wherein the second match threshold is 15.

Example 28 includes the at least one non-transitory computer readablemedium of example 15, wherein the instructions, when executed, cause theat least one processor to determine a timestamp for the second signatureof the stitched signature based on the time data of the signatures ofthe first candidate.

Example 29 includes a method, comprising determining an alignment pointof a first candidate signature segment and a second candidate signaturesegment, the first candidate signature segment and the second candidatesignature segment including time data and signature data, the alignmentpoint based on the time data of the first candidate signature segmentand the time data of the second candidate signature segment, comparing afirst signature to a second signature at the alignment point, the firstsignature included in the first candidate signature segment and thesecond signature included in the second candidate signature segment, andstitching the second signature to the first signature based on thecomparison to generate a stitched signature, the stitched signature usedfor media crediting.

Example 30 includes the method of example 29, further includingdetermining whether the first candidate signature segment and the secondcandidate signature segment meet a candidate duration threshold.

Example 31 includes the method of example 30, further includingdetermining the candidate duration threshold based on at least one ofvalidation data or a stitching ability.

Example 32 includes the method of example 29, further includingdetermining a strong match between the first candidate signature segmentand the second candidate signature segment in response to a differencebetween the first signature and the second signature being less than afirst deviation threshold.

Example 33 includes the method of example 32, wherein the firstdeviation threshold is one.

Example 34 includes the method of example 29, further including countinga number of strong matches between the first candidate signature segmentand the second candidate signature segment.

Example 35 includes the method of example 34, further includingidentifying a basic match between the first candidate signature segmentand the second candidate signature segment in response to the number ofstrong matches exceeding a first match threshold.

Example 36 includes the method of example 35, wherein the first matchthreshold is four.

Example 37 includes the method of example 35, further includingdetermining the basic match in response to a difference between thefirst signature and the second signature being less than a seconddeviation threshold.

Example 38 includes the method of example 37, wherein the seconddeviation threshold is two.

Example 39 includes the method of example 34, further including countinga number of basic matches between the first candidate signature segmentand the second candidate signature segment.

Example 40 includes the method of example 39, further includingstitching the second candidate signature segment to the first candidatesignature segment to generate a stitched signature in response to thenumber of basic matches exceeding a second match threshold.

Example 41 includes the method of example 40, wherein the second matchthreshold is 15.

Example 42 includes the method of example 29, further includingdetermining a timestamp for the second signature of the stitchedsignature based on the time data of the signatures of the firstcandidate.

Example 43 includes an apparatus, comprising at least one storagedevice, and a processor circuitry to determine an alignment point of afirst candidate signature segment and a second candidate signaturesegment, the first candidate signature segment and the second candidatesignature segment including time data and signature data, the alignmentpoint based on the time data of the first candidate signature segmentand the time data of the second candidate signature segment, compare afirst signature to a second signature at the alignment point, the firstsignature included in the first candidate signature segment and thesecond signature included in the second candidate signature segment, andstitch the second signature to the first signature based on thecomparison to generate a stitched signature, the stitched signature usedfor media crediting.

Example 44 includes the apparatus of example 43, wherein the processorcircuitry is to determine whether the first candidate signature segmentand the second candidate signature segment meet a candidate durationthreshold.

Example 45 includes the apparatus of example 44, wherein the processorcircuitry is to determine the candidate duration threshold based on atleast one of validation data or a stitching ability.

Example 46 includes the apparatus of example 43, wherein the processorcircuitry is to determine a strong match between the first candidatesignature segment and the second candidate signature segment in responseto a difference between the first signature and the second signaturebeing less than a first deviation threshold.

Example 47 includes the apparatus of example 46, wherein the firstdeviation threshold is one.

Example 48 includes the apparatus of example 43, wherein the processorcircuitry is to count a number of strong matches between the firstcandidate signature segment and the second candidate signature segment.

Example 49 includes the apparatus of example 48, wherein the processorcircuitry is to identify a basic match between the first candidatesignature segment and the second candidate signature segment in responseto the number of strong matches exceeding a first match threshold.

Example 50 includes the apparatus of example 49, wherein the first matchthreshold is four.

Example 51 includes the apparatus of example 49, wherein the processorcircuitry is to determine the basic match in response to a differencebetween the first signature and the second signature being less than asecond deviation threshold.

Example 52 includes the apparatus of example 51, wherein the seconddeviation threshold is two.

Example 53 includes the apparatus of example 48, wherein the processorcircuitry is to count a number of basic matches between the firstcandidate signature segment and the second candidate signature segment.

Example 54 includes the apparatus of example 53, wherein the processorcircuitry is to stitch the second candidate signature segment to thefirst candidate signature segment to generate a stitched signature inresponse to the number of basic matches exceeding a second matchthreshold.

Example 55 includes the apparatus of example 54, wherein the secondmatch threshold is 15.

Example 56 includes the apparatus of example 43, wherein the processorcircuitry is to determine a timestamp for the second signature of thestitched signature based on the time data of the signatures of the firstcandidate.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

The following claims are hereby incorporated into this DetailedDescription by this reference, with each claim standing on its own as aseparate embodiment of the present disclosure.

What is claimed is:
 1. An apparatus comprising: first means fordetermining an alignment point of a first candidate signature segmentand a second candidate signature segment, the first candidate signaturesegment and the second candidate signature segment including time dataand signature data, the alignment point based on the time data of thefirst candidate signature segment and the time data of the secondcandidate signature segment; means for comparing a first signature to asecond signature at the alignment point, the first signaturerepresentative of media included in the first candidate signaturesegment, the second signature representative of media included in thesecond candidate signature segment; and means for stitching the secondsignature to the first signature based on the comparison to generate astitched signature, the stitched signature to be used for mediacrediting.
 2. The apparatus of claim 1, further including second meansfor determining whether the first candidate signature segment and thesecond candidate signature segment meet a candidate duration threshold.3. The apparatus of claim 1, wherein the means for comparing is todetermine a strong match between the first candidate signature segmentand the second candidate signature segment in response to a differencebetween the first signature and the second signature being less than afirst deviation threshold.
 4. The apparatus of claim 1, furtherincluding means for counting a number of strong matches between thefirst candidate signature segment and the second candidate signaturesegment.
 5. The apparatus of claim 4, wherein the means for comparing isto identify a basic match between the first candidate signature segmentand the second candidate signature segment in response to the number ofstrong matches meeting a first match threshold.
 6. The apparatus ofclaim 4, wherein the means for counting is to count a number of basicmatches between the first candidate signature segment and the secondcandidate signature segment.
 7. The apparatus of claim 6, wherein themeans for stitching is to stitch the second candidate signature segmentto the first candidate signature segment to generate a stitchedsignature in response to the number of basic matches meeting a secondmatch threshold.
 8. A method, comprising: determining an alignment pointof a first candidate signature segment and a second candidate signaturesegment, the first candidate signature segment and the second candidatesignature segment including time data and signature data, the alignmentpoint based on the time data of the first candidate signature segmentand the time data of the second candidate signature segment; comparing afirst signature to a second signature at the alignment point, the firstsignature representative of media included in the first candidatesignature segment, the second signature representative of media includedin the second candidate signature segment; and stitching the secondsignature to the first signature based on the comparison to generate astitched signature, the stitched signature to be used for mediacrediting.
 9. The method of claim 8, further including determiningwhether the first candidate signature segment and the second candidatesignature segment meet a candidate duration threshold.
 10. The method ofclaim 8, further including determining a strong match between the firstcandidate signature segment and the second candidate signature segmentin response to a difference between the first signature and the secondsignature being less than a first deviation threshold.
 11. The method ofclaim 8, further including counting a number of strong matches betweenthe first candidate signature segment and the second candidate signaturesegment.
 12. The method of claim 11, further including identifying abasic match between the first candidate signature segment and the secondcandidate signature segment in response to the number of strong matchesmeeting a first match threshold.
 13. The method of claim 11, furtherincluding counting a number of basic matches between the first candidatesignature segment and the second candidate signature segment.
 14. Themethod of claim 13, further including stitching the second candidatesignature segment to the first candidate signature segment to generate astitched signature in response to the number of basic matches meeting asecond match threshold.
 15. An apparatus, comprising: memory; computerreadable instructions; and processor circuitry to execute the computerreadable instructions to: determine an alignment point of a firstcandidate signature segment and a second candidate signature segment,the first candidate signature segment and the second candidate signaturesegment including time data and signature data, the alignment pointbased on the time data of the first candidate signature segment and thetime data of the second candidate signature segment; compare a firstsignature to a second signature at the alignment point, the firstsignature representative of media included in the first candidatesignature segment, the second signature included in the second candidatesignature segment; and stitch the second signature to the firstsignature based on the comparison to generate a stitched signature, thestitched signature to be used for media crediting.
 16. The apparatus ofclaim 15, wherein the processor circuitry is to determine a strong matchbetween the first candidate signature segment and the second candidatesignature segment in response to a difference between the firstsignature and the second signature being less than a first deviationthreshold.
 17. The apparatus of claim 15, wherein the processorcircuitry is to count a number of strong matches between the firstcandidate signature segment and the second candidate signature segment.18. The apparatus of claim 17, wherein the processor circuitry is toidentify a basic match between the first candidate signature segment andthe second candidate signature segment in response to the number ofstrong matches meeting a first match threshold.
 19. The apparatus ofclaim 17, wherein the processor circuitry is to count a number of basicmatches between the first candidate signature segment and the secondcandidate signature segment.
 20. The apparatus of claim 19, wherein theprocessor circuitry is to stitch the second candidate signature segmentto the first candidate signature segment to generate a stitchedsignature in response to the number of basic matches meeting a secondmatch threshold.